Beamforming is a signal processing technique for increasing signal-to-noise ratio (SNR) through directional or spatial selectivity of signals transmitted through an array of antennae or transducers or received from an array of sensors. In traditional delay-and-sum beamforming, signals from multiple sensors are delayed according to distance to the focus point of the beamformer and the speed-of-sound in the medium and are summed to provide a beamformed signal with increased signal-to-noise ratio. While the traditional delay-and-sum beamformer works in environments where these delays are well known, e.g., free-field acoustic environments, or homogeneous media that are free of reflectors and scatterers, delay-and-sum beamforming fails in reverberant environments, because the time delays between sensor elements are generally unknown based solely on distance and speed-of-sound and are dependent on the frequency response and acoustic properties of the acoustic environment. If the environment is not homogeneous in its properties, delays calculated based solely on geometry and an average speed-of-sound can result in reduced signal-to-noise ratio after beamforming.
The use of delay-and-sum beamforming in medical ultrasound is commonly known. Traditional delay-and-sum beamforming of signals transmitted and received by individual elements using fixed delays counteracts dispersion of the transmitted and received signals and focuses the beam. FIG. 1A is a schematic diagram showing illustration of beamforming a transmit signal to focus ultrasound on a point, and FIG. 1B is a schematic diagram showing illustration of beamforming the reflected signal to focus the expanding wavefront generated by a scatterer in the tissue. In FIGS. 1A and 1B, each rectangular element 108, 114 in the vertical line constitutes an array element. In FIG. 1A, a synchronous series of pulses 102, delayed appropriately by delay lines 104 to produce delayed transmit pulses 106 at array elements 108, causes a converging pressure wave to focus on a particular point in the tissue 110. As the wave passes boundaries of varying acoustic impedance, some energy is transmitted and some is reflected. The transmitted signal is beamformed to “steer” the beam to a focus point. In FIG. 1B, echoes 112 of the beam off of a reflector at that point are received at array elements 114 and the transduced echoes 116 are phase-aligned by delay lines 118 to produce phase-aligned echoes 120 that are beamformed by summer 122 to produce beamformed signal 124, generally using the same transducers as used to transmit the pulse (i.e., array elements 108 and 114 may be the same array elements). In pulse-echo ultrasound, time delays between signals reaching individual elements of a transducer or probe array are computed given the distance to the focus point and an average speed of sound in the tissue. Like acoustic beamforming systems, performance of delay-and-sum beamforming in ultrasound systems suffers from a number of factors, including the difference in speed of sound among different tissue types, and multiple unknown scatterers distributed through the tissue that contribute to the return signal.
In state-of-the-art ultrasound, the beamforming delays (τi in FIG. 1) in transmitting and receiving the pulse are generally fixed by distance and speed-of-sound in the tissue c and are implemented through a combination of analog and digital circuitry. The speed of sound is assumed to be fixed and is based largely on the speed of sound in water and a variety of tissues. However, the speed of sound in tissue varies significantly. The difference in speed of sound between various types of tissue encountered during imaging is a result of variations in compressibility and density, and it is known that the speed of sound in tissue is not constant, but may range, for example from ˜1350-1600 m/s (J. Greenleaf and R. Bain, Clinical Imaging with Transmissive Ultrasonic Computerized Tomography, IEEE Trans. On Biomedical Imaging, BME-28(2), February 1981). Traditional delay-and-sum beamforming in such environments results in reduced resolution and contrast, owing to errors in focusing the transducer array on a desired location and uncertainty in origin of the contribution of the echo; fixed delays and speed of sound thus cause a “spread” in the point of focus that reduces resolution achieved in transmit and receive functions.
This point spread function (PSF) of an imaging system is its response to a point input, or spatial impulse response. A point input is the smallest pixel (2D) or voxel (3D) in the idealized image, and the PSF is the spread of the point input over a region, generally more than a single pixel/voxel in the actual image; in addition to speed of sound considerations, because the tissue is filled with scatterers, the energy at each voxel includes a contribution from many other voxels eroding the contribution from the voxel of focus. Hence, each voxel must have energy focused on it alone, as best as possible (by beamforming) to reduce scatter, and the receive function must also focus on receiving energy from that voxel as best as possible. The characteristics of the PSF in the direction of the beam depend on the center frequency and bandwidth of signals transmitted by each element of the array. The characteristics laterally and in elevation depend on element spacing, aperture of the beam and electronic beamforming performed to focus the transmit and receive beams. Resolution in an ultrasound image depends on the number of probe elements, their spacing, the probe excitation frequency f or wavelength λ, and the spatial pulse length (SPL) n, where n is the number of cycles in the pulse. For a given f and SPL, physical realization of this resolution depends on the degree to which energy can be focused on a tissue voxel, and the degree to which received reflections can be aligned through electronic beamforming.
The number of elements in an ultrasound transducer also affects the image through the appearance of grating lobes associated with spatial sampling. Additionally, incoherence between probe transducer elements spaced far apart reduces the ability to determine time delays between these elements. Therefore, common practice in beamforming large ultrasound transducer arrays incorporates apodization—weighting the contribution from each element of the array—and is required to minimize grating lobes, a form of spatial aliasing that occurs when the spacing between elements d≧λ/2. Element size is fundamentally a manufacturing issue, i.e., there are physical limits to d. The fewer the number of elements used to beamform, the larger the gain in the direction of grating lobes. Apodization, e.g., using a Hamming window, minimizes the effect of grating lobes (spatial aliasing) inherent in beamforming with high frequency probes by de-weighting the contribution of elements on the fringes of the array, which then diminishes the contribution of these elements to the gain and limits the gain achieved through beamforming.
FIGS. 2A-2C show polar plots of the beampatterns for some exemplary forward-looking arrays of elements with and without apodization. In these examples, probe frequency is 10 MHz and element spacing is 1.25λ. FIG. 2A shows the beampatterns for an exemplary array of 32 elements without apodization, as known in the art. FIG. 2B shows the beampatterns for an exemplary array of 32 elements with Hamming window apodization, as known in the art. A 32-element probe with apodization to reduce grating lobes suffers from power loss of 5 dB. FIG. 2C shows the beampatterns for an exemplary array having 512 elements without apodization, as known in the art. A 512 element probe with identical element spacing has inconsequential grating lobes, and power increases by 30 dB over the 32-element probe with apodization. Beamwidth also decreases with increase in number of elements, demonstrating increase in resolution.
As a signal propagates through a reflector, “echoes” result from a transmitted signal reflecting off the front and rear boundary of a tissue feature. As the size of the feature decreases, the delay between reflections decreases, providing a feature size limit. The axial resolution measures the potential to distinguish between two features that are closely spaced in the axial direction. It is given by SPL/2 and is constant along the signal propagation path into the tissue. Features that are adjacent to each other along the signal path must be separated be at least SPL/2 to appear distinct. This is based on the round trip distance between two distinct reflectors and assures that the return echo from the further reflector passes the nearer reflector after the end of the pulse passes through the nearer reflector. n=2-4 cycles are used in the transmit signal; the best case (shortest pulse) axial resolution occurs for n=1 and is
      θ    z    =            λ      2        =                  c                  2          ⁢          f                    .      The lateral spatial resolution,
            θ      x        =          sin      ⁡              (                  λ          D                )              ,is the resolution perpendicular to the beam and determines the minimum distance required between two side-by-side features that results in two distinct echoes. D is the diameter of the array defined as Md for a linear array with M elements of spacing d. Decreasing wavelength, i.e., a higher frequency probe, and increased number of probe elements, provide increased resolution axially and laterally. With a 5-10 MHz probe, the wavelength is sub-mm; however, imaging through several cm of tissue is difficult owing to the signal losses as penetration depth increases. To work at high probe frequencies, signal amplification is required to maintain sufficient signal-to-noise ratio and contrast-to-noise ratio in the image, as discussed below.
Adaptive beamforming, in which delays are estimated, can improve focusing and is not dependent on knowing the speed-of-sound along the beam path. Improved electronic focusing through adaptive beamforming, both in time (reducing error in time delays) and in space (beamforming of orders of magnitude more sensor elements than present technology), is required to improve resolution. By reducing time delay uncertainty, the resolution achieved becomes largely dependent on geometry, spatial pulse length (SPL), and probe frequency and is described by a voxel in space, with lateral, axial, and elevation components. However, in systems with a large number of sensor elements, such as ultrasound transducer arrays, there is no known method from the prior art to manage the computation required for adaptive beamforming in real time or near real time to produce images in real time or near real time. Prior art adaptive beamforming systems suffer from lack of scalability as the number of channels increases. As the number of channels increases, the complexity of the computations required to add the signals coherently grows, as each channel must be correlated with each other channel, shifted in time, and summed. The complexity of estimating time delays using adaptive filters also grows in relation to the number of transducer elements. Additionally, incoherence between probe transducer elements spaced far apart reduces the ability to determine time delays between these elements, either based on distance and speed-of-sound or using adaptive time delay estimation.
Existing systems for beamforming generally use digital signal processors but are limited in throughput by the speed of the processor, the capacity and throughput of the data bus, and the number of input/output channels the DSP device may accommodate. Accordingly, prior beamforming systems have generally been limited in number of channels in order to permit real-time or near real-time processing.
There are physical limits on energy that can be put into the tissue on the transmit cycle to avoid tissue heating; therefore, the signal amplification should occur on the reflected signal. The beamforming process amplifies the signal relative to the noise providing a theoretical maximum signal gain of 10 log M; hence, beam-forming as many elements simultaneously as possible, increases SNR in the reflected signal. This in turn translates to improved image contrast. Current probes have 128 to 256 elements or more, but do not beamform all signals simultaneously owing to as-of-yet insurmountable technical issues with high frequency sampling and pushing terabytes of data through beamforming signal processing channels. Beamforming is generally performed using analog electronics on 32-64 elements at a time and apodization described above.
It should be noted that the foregoing figures and the elements depicted therein are not necessarily drawn to consistent scale or to any scale. Unless the context otherwise suggests, like elements are indicated by like numerals.